Model Generation from Multiple Volumes Using Constrained Elastic SurfaceNets

Abstract

Three dimensional models of anatomical structures are currently used to aid in medical diagnosis, treatment, surgical guidance, and surgical simulation. Limitations on the resolution of medical scans can cause artifacts to appear in the models that do not exist in the patient’s anatomy. The most severe artifacts occur due to the low sampling rate between image slices of a scan. This paper describes a method of combining two orthogonal scans to generate a model with higher resolution than models created from either of the scans alone. The two scans are first registered to each other and then a net of linked surface nodes is initialized for each of the scans. The nodes from the two nets are then merged and relaxed, subject to constraints set by the resolution of each scan. This generates a smooth surface representation which stays faithful to the original binary data.